Journal of Cardiovascular Computed Tomography
Volume 3, Issue 6 , Pages 372-382, November 2009

Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography

  • Damini Dey, PhD

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
    • Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
    • Corresponding Author InformationCorresponding author.
  • ,
  • Victor Y. Cheng, MD

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
  • ,
  • Piotr J. Slomka, PhD, FCCPM, FACC

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
    • Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
  • ,
  • Ryo Nakazato, MD

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
  • ,
  • Amit Ramesh, MSc

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
  • ,
  • Swaminatha Gurudevan, MD

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
  • ,
  • Guido Germano, PhD, FACC

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
    • Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
  • ,
  • Daniel S. Berman, MD, FACC

      Affiliations

    • Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA
    • Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

Received 17 April 2009; accepted 16 September 2009. published online 05 October 2009.

Introduction

We aimed to develop an automated algorithm (APQ) for accurate volumetric quantification of non-calcified (NCP) and calcified plaque (CP) from Coronary CT angiography (CCTA).

Methods

APQ determines scan-specific attenuation thresholds for lumen, NCP, CP and epicardial fat, and applies knowledge-based segmentation and modeling of coronary arteries, to define NCP and CP components in 3D. We tested APQ in 29 plaques for 24 consecutive scans, acquired with dual-source CT scanner. APQ results were compared to volumes obtained by manual slice-by-slice NCP/CP definition and by interactive adjustment of plaque thresholds (ITA) by 2 independent experts.

Results

APQ analysis time was <2 sec per lesion. There was strong correlation between the 2 readers for manual quantification (r = 0.99, p < 0.0001 for NCP; r = 0.85, p < 0.0001 for CP). The mean HU determined by APQ was 419 ± 78 for luminal contrast at mid-lesion, 227 ± 40 for NCP upper threshold, and 511 ± 80 for the CP lower threshold. APQ showed a significantly lower absolute difference (26.7 mm3 vs. 42.1 mm3, p = 0.01), lower bias than ITA (32.6 mm3 vs 64.4 mm3, p = 0.01) for NCP. There was strong correlation between APQ and readers (R = 0.94, p < 0.0001 for NCP volumes; R = 0.88, p < 0.0001, for CP volumes; R = 0.90, p < 0.0001 for NCP and CP composition).

Conclusions

We developed a fast automated algorithm for quantification of NCP and CP from CCTA, which is in close agreement with expert manual quantification.

Keywords: Coronary artery segmentation, Coronary CT angiography, Coronary plaque, Noncalcified and calcified plaque, Plaque characterization, Plaque quantification

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 Conflict of interest: The authors report no conflicts of interest.

 This study was supported by American Heart Association Grant-in-Aid Award 09GRNT2330000, by a grant from the Lincy Foundation, and in part by grant 6318 from the Glazer Foundation, Los Angeles, CA.

PII: S1934-5925(09)00505-X

doi:10.1016/j.jcct.2009.09.004

Journal of Cardiovascular Computed Tomography
Volume 3, Issue 6 , Pages 372-382, November 2009